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Show Daily | Exploring the risk-based approach to de-identification Related reading: Evaluating the use of AI in privacy program operations





As with so many things in this world, there is rarely, if ever, a silver-bullet solution to a complex problem in privacy. Perhaps the most glaring example of this is in defining the identifiability of an individual. Countless privacy laws and regulations around the world define personal information in different ways using varying definitions. Though not new, de-identification, or anonymization, is a useful tool to meet compliance and mitigate risk. "Identifiability is relative and contextual," Mike Hintze, CIPP/C, CIPP/E, CIPP/G, CIPP/US, CIPM, CIPT, FIP, pointed out to a room full of privacy pros during an Active Learning session Tuesday here at the Summit. Together with the Future of Privacy Forum's Kelsey Finch, CIPP/US, Privacy Analytics' Khaled El-Emam, and Lucid Privacy's Colin O'Malley, he demonstrated the value of thinking about the risk-based approach to de-identification. Jedidiah Bracy, CIPP, has the story for Privacy Tech.
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